Role of Cooperatives in Empowering Rural Women

Developing Country Studies www.iiste.org
ISSN 2224-607X (Paper) ISSN 2225-0565 (Online)
Vol.4, No.15, 2014
53
Contributions of Cooperative Movement to Alleviation of Poverty
among Rural Women: Case Study of Oriade Local Government in
Nigeria
Mrs. Mary Modupe Fasoranti, PhD
Department of Economics, Adekunle Ajasin University, Akungba Akoko, Ondo State, Nigeria
Email:olafasoranti@yaho.co.uk
Abstract
Poverty is rampant in Nigeria especially amongst rural women, which has therefore affected the quality of life of
rural women. It is now widely recognized that poverty is a worldwide problem that affects mostly rural women
in the whole world. The research study investigated the impact of Cooperative Movement on poverty alleviation
in Oriade Local Government. Data was sourced from both secondary and primary sources. The secondary source
includes relevant text books and learned journals. The primary source involves the administration of structured
questionnaire on 200 randomly selected women in the study area. The descriptive method of analysis involved
the use of tables, simple percentages. The quantitative analysis employed was the Logit regression analysis. The
study showed that cooperative movements have significant influence on poverty reduction amongst rural women
in Oriade Local Government. Also that cooperative movement will lead to economic position of the
respondents. . Moreover study showed that a respondent is likely to escape poverty by using the loan gotten from
the cooperative to purchase assets and invest in business and he is likely to remain poor by not purchasing assets
even when he belongs and benefits from the cooperative movement. The study concludes that cooperative
movement has been identified to be one of the key players in the financial industry that has positively affected
the lives of rural community dwellers. The study therefore recommends that cooperative society should also
encourage their members to use the money gotten from the cooperative to buy more of assets instead of using in
mainly on consumption.
Keywords: Poverty, Rural women, cooperative movement
Introduction:
For decades, poverty has become a global issue and a major contending force against the pace of development in
the less developed countries. Poverty has been described as the basic malady of the less developed countries
(Gerald Mier, 2001 ). Generally, poverty is quite dehumanizing as the poor lacks influence, is lowly esteemed,
has a limited range of economic and social opportunities and for most times suffers psychological defeat.
Unfortunately, the poor are generally located in the rural areas where they are primarily engaged in agriculture
and agriculturally related activities (Todaro, 2006). Most importantly, women make up a substantial majority of
the world’s poor. Women and children experience the harshest of deprivation. They are more likely to be poor
and malnourished and less likely to receive medical services, clean water, sanitation and other benefits (Irene,
1990; Judith Bruce and Daisy Dwyerreds, 1988 and Diane Eldon,1993). Among other things, from NBS (1999)
reports, rural poverty has increased both in depth and severity possibly due to the increase in rural household size
and Awoyemi (2010) showed that 32.2% of female headed households were poor while about 53.6% of male
counterparts were poor indicating that the incidence of poverty was highest around male-headed households in
the rural Nigeria. Their study also showed that the socio-economic characteristics of the family heads such as
gender, education, age and occupation are important determinants of incidence of poverty in the rural areas. Also
the study established that the incidence of poverty was highest in North Eastern Nigeria while South West has
the least.
The rural areas are characterized by vicious cycle of poverty, showing low income, low productivity, low
savings, low capital formation and low investment. Among other things, the rural areas experienced social,
economic, cultural, political and environmental deprivation. Basic infrastructural such as electricity, water,
adequate health facilities are often absent in such areas. Most importantly, is the lack of access to credit for the
financing of their business and form activities.
Oftentimes, rural dwellers find it difficult to access credit facilities from the formal financial sectors due to their
inability to produce required collateral securities. Loans from the sector are often accompanied with high interest
rates which make such loans unprofitable for the poor small holders.
Little wonder, most rural women have resorted into farming cooperative societies to bridge the financial gap.
Most women in the rural areas engage in petite business and farm works as their major sources of survival.
Given that the formal financial institutions have refused to provide financial assistance due to strict conditions,
the cooperative societies have readily provided a good alternative means of improving the quality of life of the
rural women. The following questions therefore come to mind

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54
- Has membership of cooperative societies helped the women to improve their business performance?
- What are the effects of cooperative movement in poverty indices in the study area?
- And does cooperative movement play a significant role in improving the quality of life of the rural women?
This study therefore consider the above question and in the process aims at examining the dimension of poverty
among rural women of Oriade Local Government of Osun State and the relevance of cooperative movement on
poverty alleviation among rural women in the study area.
Review of Literature
Poverty has been seen as a hydra-headed concept that means different things to different people under different
dispensations. It is generally associated with condition under which people live. It is easier to identify the
dimension of poverty than giving a straight line definition of what poverty is. Poverty is seen as a state of
involuntary deprivation that a person, household and society may be subjected to (Ogwumike, 2001, Odusola,
2001; Ojo 1995; Madinagu, 1999; and Enjlama and Bamide , 1997) while others see it as inability to meet basic
material needs such as food, water, clothing, shelter, education and health and also lack of non-material needs
such as participation, identity, dignity, self esteem, freedom and sustenance
Poverty can be reflected in different dimensions. Accordingly to Jhinjan (2006), Sen (1999) and World Bank
(2001), the followings are the reflections of poverty.
- Lack of freedom of action and choice
- Lack of adequate food and shelter, education and health
- Vulnerability to ill-health, natural disasters.
- The poor is economically disadvantaged in that she has limited range of social and economics
opportunities.
- The poor is powerless, voiceless and lacks influence and of low status.
Poverty can be measured in different. The most important ones can be grouped into three
- Income
- Assets – money at hand , securities, real estates, money in banks
- Socio-economic metrics – health, nutrition, infant immortality, sanitation accessibilities to water,
electricity, education, decent clothing, freedom, self esteem and other aspects of human well being.
However, what indices are used to measure poverty varies depending on the level of development and
availability of data. As sourced from infoplease.com, data on the first category of information is readily
available, reliable and relevant especially in the developed countries.
Moreover, income inequality is the major underlying issue in poverty in such countries. The indices under the
third category are quite relevant in the Third world countries. Families that have access to them are considered
well off whereas such people in developed countries are considered poor because they have little else and those
things that are essentials in developed countries. For example, a house without plumbing is not legally fit for
dwelling. Public education is compulsory for children and there are health and food programmes that guaranteed
adequate levels of health care, environmental sanitation and nutrition. This study adopts the third category of
indices of poverty.
Cooperative movement dated back to 1894 when the Rochdale Equitable Pioneers Society was established in
Rochdale, England. Ever since then, the movements have spread to all countries of the world under different
names. In Nigeria, the movement started among the Yorubas under the concept of Igbe Dide ( joint hunting),
joint farming, fishing etc. all these were capture Owe. Owe is normally among peer groups for community
service, personal work or for the payment of bridal price to in-laws. With the increase in development, the
principle of Owe has moved from rendering physical labour to that of financial cooperative under the name Egbe
Alajeseku (association of people who do not consume all their income). The background of cooperative
movement cold be traced to the traditional savings and loans system. The movement started in the agricultural
sector and late spread to other sectors. Today, a cooperative movement is a common phenomenon in the
Nigerian society – the real old service sectors.
The most important fact is that rural women have been the prominent members of cooperative societies
everywhere. In Nigeria today, the major forms of cooperative societies include
- Consumers’ cooperative societies
- Produce cooperative societies
- Agricultural cooperative societies
- Housing cooperative societies
- Artisan and industrial cooperative societies
- Credit and thrift cooperative societies
- Professional cooperative societies
The focus of this study is on the effect of thrift cooperative societies on poverty indices of women in the study
area. The thrift cooperative society is one in which members contribute a portion of their income before they

Vol.4, No.15, 2014
55
have access to loans. Members are usually people whose incomes are the same. The role of cooperative
movements in improving the lots of rural dwellers cannot be over emphasized. From Abdul-Yakeen (2012), the
following advantages could be identified
- Mobilization and distribution of capital
- Creation of employment and income generating opportunity
- A forum for education and training and solidarity schemes to cater for unexpected expenses relating to
illness, social welfare, death etc
- Help to increase the productivity and incomes of small scale farmers through collective negotiation of
better prices for their products, seeds, fertilizer, transport and storage, and expansion of market’s
accessibility.
In our contemporary times, most business depends on loans from cooperative societies. This study therefore
considers the effects of such societies on poverty alleviation among rural women. This is a departure from other
studies that considered the general effects of cooperative societies.
Methodology
i. Area of Study
The study was in conducted Oriade Local Government of Osun State. Oriade is a Local Government area in the
northeastern part of Osun state. It is predominantly occupied by the Ijesa people; its capital is Ijebu-Jesa. Women
in towns like Ipetu Ijesa, Ikeji Ile, and Ikeji-Arakeji work are mat weavers. This is derived from local long grass
called "Eni" in the local dialect. It has an area of 465 km2
and a population of 148,617 at the 2006 census. There
are tourist’s sites such as Oluminrin Water Falls among others. The predominant economic activity they engage
in is cultivation of cocoa. They practice cooperative movement through “Esusu”.
ii. Sources of data, sampling method and sample size
The study employed both primary and secondary sources of data. Primary source involved the use of well
structured questionnaire to obtain relevant information from respondents in the study area. Secondary sources
employed were relevant journals and textbooks. Data was collected from 200 randomly selected women from
two villages namely Ijebu-Jesa and Ikeji-Arakeji. The choice of the two villages was based on the popularity of
cooperative movement in the area. The information on variables such as age; income; sex; educational status;
major occupation and some selected indices of poverty.
iii. Method of analysis
The study used descriptive and quantitative statistics to analyze the information collected from respondents in
the study area. Descriptive statistics used were frequency distribution, chats, tables and percentages. Quantitative
method used was the binary logistic linear regression analysis. The hypothesis was analyzed via evaluation of
relevant statistics associated with the numerical values of model parameters vis-à-vis their critical values
contained in the tables.
iv. Model specification
The binary logistic model specified for the study is as follows.
ln(ODDS) = ln = a + bX ………………………………..1
P = ………………………………..2
ODDS is ℮a+bx
dPi = ℮a+bx
Ii.
dXji (1+℮a+bx
)2 X
ji
Where Pi = the probability of ith benefiting from cooperative movement
Xi = vector of explanatory variables
When simplified, the model becomes:
Ῠi = g (Ii) , and = 0 + bjX ………………………………………………………4
Where Ῠi = the observed response for the ith observation (i.e. the binary variable, Ῠi = 2 (yes) for using the loan
gotten to purchase assets, and improve their standard of living and Ῠi = 1(no) for Otherwise
Ii = underlying and observed stimulus index for the ith

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56
g = is the functional relationship between the field observation (Yi) and the stimulus index (Ii) which
determines the probability of reducing poverty.
The logit model assumes the underlying stimulus index (Ii) is a random variable, which predicts the probability
of reducing poverty. Therefore, for the ith observation (an individual rural woman in cooperative moment):
=
P
1−P
0 + bjX ………………………………………………………………..5
dPi = eI
i Ii
dXji (1+eI
i)2 X
ji
Where Pi = the probability of ith using the loan to acquire assets, and improve their standard of living
Xi = vector of explanatory variables
X1 = Assets acquired. (Yes, no)
X2 = Source Water (well, rain, borehole, pipe borne water, stream)
X3 = Cooking Methods (Stove, Coal Pot, Gas and Firewood)
X4 = Type of energy source (Kerosine, Fire wood, Gas)
X5 = Household Feeding Pattern (1:1:0, 1:0:1, 0:1:0, 1:1:1, 0:0:1)
Data analysis and interpretation
Age Distribution of Respondents.
Table 1: Distribution of Respondents by Age
Age range Frequency Percent Cumulative Percent
Below or 20 2 1.0 1.0
21 – 30 30 15.0 16.0
31 – 40 56 28.0 44.0
41 – 50 69 34.5 78.5
Above 51 43 21.5 100.0
Total 200 100.0
Source: Field survey (2013) X = 36.1
The table above shows that 2 of the respondents representing 1% are below or 20 years of age, 30 respondents
representing 15% fall between the ranges of 21-30 years. 56 of them representing 28% fall between 31-40 years,
69 of them representing 34.5% fall between 41-50 years while 43 of them representing 21.5% are above 55 years.
This implies that majority of the respondents fall within the age range of 31-40 years and 21-30 years. The table
shows that about 77% of total respondents are between 21 and 50 years old implying that majority are still within
their economically active years. The mean age stood at 36 years.
Sex Distribution of Respondents.
Table 2 Distribution of Respondents by Marital Status
Marital Status Frequency Percent Cumulative Percent
Single 14 7.0 7.0
Married 154 77.0 84.0
Divorced 3 1.5 85.5
Separated 1 .5 86.0
Widowed 28 14.0 100.0
Total 200 100.0
Source: Field survey (2013)
The above table shows that 14 representing (7%) of the respondents were singles, 154 representing (77.5%) of
the respondents were married, 3 representing (1.5%) of the respondents were divorced, 1 representing (0.5%) of
the respondents were separated, while 28 representing (14%) of the respondents were widowed. The table shows
there are more married in the respondents.

Vol.4, No.15, 2014
57
Educational Distribution of Respondents.
Table 3 Distribution of Respondents by Educational Qualification
Frequency Percent Cumulative Percent
No Formal Education 7 3.5 3.5
Primary School 36 18.0 21.5
SSCE 51 25.5 47.0
OND/NCE 45 22.5 69.5
HND/B.Sc 61 30.5 100.0
Total 200 100.0
From the above table, it shows that 7 (3.5%) of the respondents have no formal education, 36 (18%) of the
respondents have qualification at primary school, 51 (25.5%) of the respondents have SSCE as highest
educational qualification, 45 (22.5%) of the respondents have qualification at OND/NCE while 61(30.5%) of the
respondents have HND/B.Sc which constitute the largest group. Given that majority of the respondents (78.5%)
are literate, there is the possibility of better usage loans obtained from the cooperative society, all things being
equal.
Distribution of Respondents by their cooking methods Cooking methods used
TABLE 4 RESPONDENTS’ COOKING METHODS
Kerosene stove 105 52.5 52.5
Coal pot 33 16.5 69.0
Gas cooker 44 22.0 91.0
Fire wood 18 9.0 100.0
Total 200 100.0
The above reveals that 52.5% of the respondents use kerosene stove to cook, 16.5% of the respondents use coal
pot to cook, 22% of the respondents use gas cooker to cook while 9% of the respondents still use fire wood to
cook.
TABLE 5 RESPONDENTS’ FEEDING PATTERN
1: 1: 0 9.0 4.5 4.5
1: 0: 1 23 11.5 16.0
1: 1: 1 168 84.0 100.0
Total 200 100.0
From the question above it was shown that 4.5% feeding pattern is 1: 1: 0, 11.5% feeding’s pattern is 1: 0: 1,
while 84% feeding’s pattern is 1: 1: 1. Study further showed that 14% of the respondents usually include Egg,
meat, beans, soya bean in their meal, 23% of the respondents often include Egg, meat, beans, soya bean in their
meal, 31% of the respondents include Egg, meat, beans, soya bean in their meal at times while 0.5% of the
respondents don’t include Egg, meat, beans, soya bean in their meal at all.
TABLE 6 Types of houses by Respondents
Mud house 3 1.5 1.5
Bungalow 40 20.0 21.5
Duplex 5 2.5 24.0
Face me I face you 17 8.5 32.5
Flat 135 67.5 100.0
Total 200 100.0
The table above reveals that 1.5% of the respondents live in mud house, 20% of the respondents live in
bungalow, 2.5% of the respondents live in duplex, 8.5% of the respondents live in face me and face you
apartment while 67.5% of the respondents live in flat. Study also revealed that 66% of the respondents lived in
rented houses while 34% owned houses.

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58
TABLE 7 Sources of water
Well 24 12.0 12.0
Borehole 37 18.5 30.5
Pipe borne water 137 68.5 99.0
Stream 2 1.0 100.0
Total 200 100.0
The question above reveals that 12% of the respondents’ source of water is well, 18.5% of the respondents’
source of water is borehole, 68.5% of the respondents’ source of water is pipe borne water, while 1% of the
respondents’ source of water is stream.
TABLE 8 Income Distribution of Respondents
Below or N50,000 36 18.0 18.0
N 50,001- N 100,000 89 44.5 62.5
Above N 100,001 75 37.5 100.0
Total 200 100.0
TABLE 9 Respondents’ monthly contributions to the Society.
Below or N 5,000 33 16.5 16.5
N 5,001 - N 10,000 49 24.5 41.0
N 10,001 - N 15,000 82 41.0 82.0
N 15,001 - N 20,000 33 16.5 98.5
Above N 20,001 3 1.5 100.0
Total 200 100.0
The above shows that 16.5% of the respondents contribute below or =N=5,000, 24.5% of the respondents
contribute between =N=5,001 to =N=10,000, 41% of the respondents contribute between =N=10,001 to
=N=15,000, 16.5% of the respondents contribute between =N=15,001 to =N=20,000, while 1.5% of the
respondents contribute above =N=20,001. The major benefits derived from the society as revealed by members
are accessibility to loans (78%) and a sense of belonging (28%).
About 83% of the respondents have obtained loans while 17% have not as the time of this study. The
loan repayment period ranged between six months and one year depending on the amount collected. Majority of
those that collected loans (28.5%) invested it in business, 23% and 26.5% used for building the purchase of car
respectively while 5% used it for personal purposes.
Most of the respondents claimed to have invested their savings in trading, non-trading and agriculturally
related ventures. About 41.7% of total respondents realized over 350,000 as income from their businesses
while 19.4% earned less than 50,000 naira and 38.9% had between 50,000 and 350,000 naira. Ninety percent of
the respondents reported that they have such income to acquire assets.
Logistic regression analysis of the contribution of cooperative movement to poverty alleviation amongst
rural women
The binary regression model was used to determine the contribution of cooperative movement on major
microeconomic variables and indices of poverty, and the result is presented in the table below
TABLE 10: Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
Assets -26.304 7222.239 .000 1 .997 .000
Source Water -48.694 2702.872 .000 1 .986 .000
Method of cooking 10.604 1673.615 .000 1 .995 40288.847
Energy source 6.143 1544.163 .000 1 .997 465.260
Feed pattern -67.565 4214.155 .000 1 .987 .000
Constant 423.191 24001.468 .000 1 .986 6.162E183
Results from the table above reveals that cooperative movement had a significant relationship and positive
relationship with poverty indices such as method of cooking and energy source. These result means that

Vol.4, No.15, 2014
59
cooperative tends to improve the cooking methods of the women because the money gotten from their savings
was used to buy modern kitchen wares. So also the analysis reveals to that cooperative movement had a negative
relationship with poverty indices like Assets, source of water, Feeding pattern. These result means that
cooperative movement has not improved the Source of water, Assets and Feeding pattern of households in the
study area.
The Variables in the Equation output shows us that the regression equation is Ln(ODDS) = 423.191 -
26.304Assets - 48.694 Source Water + 10.604 Method of cooking + 6.143 Energy source - 67.565 Feeding
pattern
As indicator for poverty this study considered the assets of respondents, the source of water of respondents,
method of cooking of respondents, energy source of the respondents, and their feeding pattern. The model
reveals the impact of each variable on poverty reduction, the value of the constant term (intercept) is 423.191.
This simply implies that if all the explanatory variables are held constant, poverty will remain 423.191. Thus,
this is the autonomous value of the poverty in the study area.
In the context of the computed elasticity (i.e. coefficients of the explanatory variables), the result suggested that,
holding the effects of other variables constant, a unit increase in assets would cause poverty to reduce by 26.304,
a unit improvement in provision of good water will cause poverty to reduce by 48.694. Similarly, a unit
improvement in feeding pattern will cause poverty to reduce by 67.565. But, looking at method of cooking it was
shown that method of cooking does not reduce poverty as improvement in cooking method would cause poverty
to increase by 10.604; also improvement in energy source would cause poverty to increase by 6.143.
We can now use this model to predict the odds that a respondent is not poor because he’s in a cooperative
movement. The odds prediction equation is;
ODDS = ℮a+bx1 +bx2 +bx3 +bx4 +bx5
Where our ‘a’ is constant and ‘b’ the value of variables used (Table 4.2.6
Variables in the Equation) If the respondent is able to use the amount gotten to purchase assets and improve in
standard of living (Yes= 2), then the ODDS is ℮423.191 - 26.304(2) - 48.694(2) + 10.604(2) + 6.143 (2) - 67.565 (2)
=4.583. That tells
us that the model predicts that the odds of escaping poverty are 4.583times higher for people who benefit from
loan and use the loan gotten from the cooperative to purchase assets, and improve their standard of living as he is
to remaining poor by not purchasing assets and improve in standard of living even when he belong and benefits
from the cooperative movement.If our respondent is not able to use the loan gotten to purchase assets, and
improve their standard of living (No=1), then our ODDS is ℮423.191 - 26.304(1) - 48.694(1) + 10.604(1) + 6.143 (1) - 67.565 (1)
=0.001. That tells us that the model predicts that the odds of remaining poor is 0.001 times higher for people
who benefit from loan but did not use the money gotten from cooperative movement to purchase assets, and
improve their standard of living.
Hypothesis Testing using the Logistic Linear Regression Analysis
The hypothesis tested is as given below.
Ho : Cooperative movement is not a significant factor in poverty reduction in the study area
As shown in table 4.2.2., given the base rates of the two cases (166/200 = 83% benefited from cooperative
movement and add to their assets, 17% who did not benefits from cooperative movement did not have much
assets), and no other information, the best strategy is to predict, for every case, that the respondents will have
more assets. Using that strategy, we would be correct 83% of the time to say cooperative movement do reduce
poverty in rural area.
Table 11 Classification Tablea,b
Observed
Predicted
Have you ever obtained loan from
the society? Percentage
CorrectYes No
Step 0 Have you ever obtained
loan from the society?
Yes 166 0 100.0
No 34 0 .0
Overall Percentage 83.0
a. Constant is included in the model.
b. The cut value is .500
As shown in table 12., given the base rates of the two cases (166/200 = 83% benefited from cooperative
movement and add to their assets, 17% who did not benefits from cooperative movement did not have much
assets), and no other information, the best strategy is to predict, for every case, that the respondents will have
more assets. Using that strategy, we would be correct 83% of the time to say cooperative movement do reduce
poverty in rural area.

Vol.4, No.15, 2014
60
Table 12 Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 0 Constant -1.586 .188 70.951 1 .000 .205
Considering table 13, the predicted odds of people who are in cooperative movement and obtain loan from the
cooperative will be 0.205. Since 34 have not benefited from cooperative movement and 166 of our respondents
have benefited from the cooperative by obtaining loan and, our observed odds are 34/166 = .205.
Table 13 Omnibus Tests of Model Coefficients
Chi-square df Sig.
Step 1 Step 176.075 6 .000
Block 176.075 6 .000
Model 176.075 6 .000
The table of Omnibus Tests of Model Coefficients presented in table 4.2.4 gives a Chi-Square of 176.075 on 6 df,
not significant beyond .000.
Decision rule
Reject H0 if constant’s P-value < Omnibus Tests’ P-value.
Where our P-value is 0.01
Decision
Since, constant’s P-value= 0.01 (gotten from Table 4.2.3 Variables in the Equation) is greater than Omnibus
Tests’ P-value=0.000 (gotten from Table 4.2.4 Omnibus Tests of Model Coefficients), we reject H0. Therefore,
it can be deduced that membership of cooperative society is a significant factor in poverty reduction in the study
area.
Model Summary
Table 14
Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square
1 110.014a
.549 .650
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.
Model Summary table shows that the -2 Log Likelihood statistic is 110.014. This statistic measures how poorly
the model predicts the decisions -- the smaller the statistic the better the model. The Cox & Snell R2
value of
0.549 shows that the cooperative loans collected accounted for about 54.9% of assets purchased, and
improvement in the standard of living by the respondents, while the remaining 45.1% of total variations are
explained by other variables not included in the model.
Summary of Findings, Conclusion and Recommendations
Summary of findings
The study investigated the contribution of cooperative movement on poverty alleviation among rural
women, in Oriade local government. Structured questionnaire was used to elicit information from 200 randomly
selected women in the study area. Data was analysed through the binary logistic regression analysis. The
analysis revealed that most respondents are in their economically active years with a mean age of 36 years.
About 93% of the respondents were educated. The test of hypothesis showed that cooperative membership was
a significant factor in poverty reduction in the study area. Model Summary table further shows the Cox & Snell
R2
value to be 0.549 which explained that the cooperative loans collected accounted for about 54.9% of assets
purchased by the respondents, while the remaining 45.1% of total variations were not explained by the model.
Results of the binary logistic model showed that cooperative loan imparted negatively on assets, sources of water
and pattern of feeding while it has positive impact on method of cooking and sources of energy. The study
showed that a respondent is likely to escape poverty at 0.125 odd by using the loan gotten from the cooperative
to purchase assets, invest and do business and he is likely to remain poor by not purchasing assets even when he
belong and benefits from the cooperative movement. And, a respondent is 2.335 times more likely to remain in
poverty by not using the money gotten from cooperative movement to purchase assets, invest and do business.
i. The odds were converted to probabilities, the model predicts that (0.700) 70% of people in cooperative
movement will continue to use the amount gotten to purchase assets, invest and do business. And, (0.111) 11%
of people participating in cooperative movement will not use the amount gotten to purchase assets, invest and do
business, and so may find it difficult to escape poverty. Conclusively one can safely say that there is a significant
relationship between cooperative movement and poverty alleviation in the study area. This therefore
recommends that the government should enlighten and educate people about the advantages of cooperative
movement in improving standard of living. Also the cooperative society should also encourage their members to
use the money gotten from the cooperative to buy more of assets instead of using it mainly on consumption.

Vol.4, No.15, 2014
61
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193-239

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Prospective authors of journals can find the submission instruction on the
following page: http://www.iiste.org/journals/ All the journals articles are available
online to the readers all over the world without financial, legal, or technical barriers
other than those inseparable from gaining access to the internet itself. Paper version
of the journals is also available upon request of readers and authors.
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Business, Economics, Finance and Management Journals PAPER SUBMISSION EMAIL
European Journal of Business and Management EJBM@iiste.org
Research Journal of Finance and Accounting RJFA@iiste.org
Journal of Economics and Sustainable Development JESD@iiste.org
Information and Knowledge Management IKM@iiste.org
Journal of Developing Country Studies DCS@iiste.org
Industrial Engineering Letters IEL@iiste.org
Physical Sciences, Mathematics and Chemistry Journals PAPER SUBMISSION EMAIL
Journal of Natural Sciences Research JNSR@iiste.org
Journal of Chemistry and Materials Research CMR@iiste.org
Journal of Mathematical Theory and Modeling MTM@iiste.org
Advances in Physics Theories and Applications APTA@iiste.org
Chemical and Process Engineering Research CPER@iiste.org
Engineering, Technology and Systems Journals PAPER SUBMISSION EMAIL
Computer Engineering and Intelligent Systems CEIS@iiste.org
Innovative Systems Design and Engineering ISDE@iiste.org
Journal of Energy Technologies and Policy JETP@iiste.org
Information and Knowledge Management IKM@iiste.org
Journal of Control Theory and Informatics CTI@iiste.org
Journal of Information Engineering and Applications JIEA@iiste.org
Industrial Engineering Letters IEL@iiste.org
Journal of Network and Complex Systems NCS@iiste.org
Environment, Civil, Materials Sciences Journals PAPER SUBMISSION EMAIL
Journal of Environment and Earth Science JEES@iiste.org
Journal of Civil and Environmental Research CER@iiste.org
Life Science, Food and Medical Sciences PAPER SUBMISSION EMAIL
Advances in Life Science and Technology ALST@iiste.org
Journal of Biology, Agriculture and Healthcare JBAH@iiste.org
Journal of Food Science and Quality Management FSQM@iiste.org
Journal of Chemistry and Materials Research CMR@iiste.org
Education, and other Social Sciences PAPER SUBMISSION EMAIL
Journal of Education and Practice JEP@iiste.org
Journal of Law, Policy and Globalization JLPG@iiste.org
Journal of New Media and Mass Communication NMMC@iiste.org
Journal of Energy Technologies and Policy JETP@iiste.org
Historical Research Letter HRL@iiste.org
Public Policy and Administration Research PPAR@iiste.org
International Affairs and Global Strategy IAGS@iiste.org
Research on Humanities and Social Sciences RHSS@iiste.org
Journal of Developing Country Studies DCS@iiste.org
Journal of Arts and Design Studies ADS@iiste.org

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